{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9edc6bcf",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "x_train.shape= (50000, 32, 32, 3)\n",
      "y_train.shape= (50000, 1)\n",
      "x_test.shape= (10000, 32, 32, 3)\n",
      "y_test.shape= (10000, 1)\n"
     ]
    }
   ],
   "source": [
    "#导入所需要的模块与包\n",
    "import tensorflow as tf\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#导入Cifar-10数据集，将训练集和测试集存储在相应变量中\n",
    "cifar10=tf.keras.datasets.cifar10\n",
    "(x_train,y_train),(x_test,y_test)=cifar10.load_data()\n",
    "#转换特征值的数据类型并进行标准化处理\n",
    "x_train,x_test=tf.cast(x_train,dtype=tf.float32)/255.0,tf.cast(x_test,dtype=tf.float32)/255.0\n",
    "#转换标签值的数据类型\n",
    "y_train,y_test=tf.cast(y_train,dtype=tf.int32),tf.cast(y_test,dtype=tf.int32)\n",
    "#显示数据集的特征值和标签值的shape属性值\n",
    "print(\"x_train.shape=\",x_train.shape)\n",
    "print(\"y_train.shape=\",y_train.shape)\n",
    "print(\"x_test.shape=\",x_test.shape)\n",
    "print(\"y_test.shape=\",y_test.shape)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "eeedc9e5",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sequential\"\n",
      "_________________________________________________________________\n",
      " Layer (type)                Output Shape              Param #   \n",
      "=================================================================\n",
      " conv2d (Conv2D)             (None, 32, 32, 32)        896       \n",
      "                                                                 \n",
      " max_pooling2d (MaxPooling2D  (None, 32, 32, 32)       0         \n",
      " )                                                               \n",
      "                                                                 \n",
      " dropout (Dropout)           (None, 32, 32, 32)        0         \n",
      "                                                                 \n",
      " conv2d_1 (Conv2D)           (None, 32, 32, 64)        18496     \n",
      "                                                                 \n",
      " max_pooling2d_1 (MaxPooling  (None, 32, 32, 64)       0         \n",
      " 2D)                                                             \n",
      "                                                                 \n",
      " dropout_1 (Dropout)         (None, 32, 32, 64)        0         \n",
      "                                                                 \n",
      " flatten (Flatten)           (None, 65536)             0         \n",
      "                                                                 \n",
      " dense (Dense)               (None, 512)               33554944  \n",
      "                                                                 \n",
      " dropout_2 (Dropout)         (None, 512)               0         \n",
      "                                                                 \n",
      " dense_1 (Dense)             (None, 256)               131328    \n",
      "                                                                 \n",
      " dropout_3 (Dropout)         (None, 256)               0         \n",
      "                                                                 \n",
      " dense_2 (Dense)             (None, 10)                2570      \n",
      "                                                                 \n",
      "=================================================================\n",
      "Total params: 33,708,234\n",
      "Trainable params: 33,708,234\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "#构建网络模型\n",
    "model=tf.keras.models.Sequential([\n",
    "#创建卷积层\n",
    "tf.keras.layers.Conv2D(32,kernel_size=(3,3),padding='SAME',activation=tf.nn.relu,input_shape=x_train.shape[1:]),\n",
    "tf.keras.layers.MaxPool2D(pool_size=(2,2),strides=(1,1),padding='SAME'),\t\t\t\t\t\t\t\t\t#创建最大池化层\n",
    "tf.keras.layers.Dropout(0.2),\t\t\t\t#创建Dropout层\n",
    "tf.keras.layers.Conv2D(64,kernel_size=(3,3),padding='SAME',activation=tf.nn.relu),\t\t\t\t\t\t#创建卷积层\n",
    "tf.keras.layers.MaxPool2D(pool_size=(2,2),strides=(1,1),padding='SAME'),\t\t\t\t\t\t\t\t\t#创建最大池化层\n",
    "tf.keras.layers.Dropout(0.2),\t\t\t\t#创建Dropout层\n",
    "tf.keras.layers.Flatten(),\t\t\t\t\t#创建拉伸层\n",
    "#创建全连接层\n",
    "tf.keras.layers.Dense(512, activation='relu'),\n",
    "tf.keras.layers.Dropout(0.2),\t\t\t\t#创建Dropout层\n",
    "#创建全连接层\n",
    "tf.keras.layers.Dense(256, activation='relu'),\n",
    "tf.keras.layers.Dropout(0.5),\t\t\t\t#创建Dropout层\n",
    "#创建全连接层作为输出层\n",
    "tf.keras.layers.Dense(10, activation='softmax')\n",
    "])\n",
    "model.summary()\t\t\t\t\t\t\t\t#显示模型各层的参数状况"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2d7f0659",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Epoch 1/10\n",
      "313/313 [==============================] - 181s 573ms/step - loss: 1.7504 - sparse_categorical_accuracy: 0.3744 - val_loss: 1.3427 - val_sparse_categorical_accuracy: 0.5304\n",
      "Epoch 2/10\n",
      "313/313 [==============================] - 180s 576ms/step - loss: 1.3046 - sparse_categorical_accuracy: 0.5332 - val_loss: 1.1339 - val_sparse_categorical_accuracy: 0.6039\n",
      "Epoch 3/10\n",
      "313/313 [==============================] - 180s 577ms/step - loss: 1.1279 - sparse_categorical_accuracy: 0.6013 - val_loss: 1.1344 - val_sparse_categorical_accuracy: 0.5985\n",
      "Epoch 4/10\n",
      "313/313 [==============================] - 184s 588ms/step - loss: 0.9942 - sparse_categorical_accuracy: 0.6536 - val_loss: 0.9850 - val_sparse_categorical_accuracy: 0.6547\n",
      "Epoch 5/10\n",
      "313/313 [==============================] - 182s 583ms/step - loss: 0.8731 - sparse_categorical_accuracy: 0.6934 - val_loss: 0.9496 - val_sparse_categorical_accuracy: 0.6726\n",
      "Epoch 6/10\n",
      "313/313 [==============================] - 183s 583ms/step - loss: 0.7596 - sparse_categorical_accuracy: 0.7342 - val_loss: 0.9243 - val_sparse_categorical_accuracy: 0.6782\n",
      "Epoch 7/10\n",
      "313/313 [==============================] - 184s 586ms/step - loss: 0.6752 - sparse_categorical_accuracy: 0.7653 - val_loss: 0.9272 - val_sparse_categorical_accuracy: 0.6882\n",
      "Epoch 8/10\n",
      "313/313 [==============================] - 182s 582ms/step - loss: 0.5671 - sparse_categorical_accuracy: 0.8007 - val_loss: 0.9638 - val_sparse_categorical_accuracy: 0.6907\n",
      "Epoch 9/10\n",
      "313/313 [==============================] - 183s 586ms/step - loss: 0.4931 - sparse_categorical_accuracy: 0.8266 - val_loss: 0.9941 - val_sparse_categorical_accuracy: 0.6890\n",
      "Epoch 10/10\n",
      "313/313 [==============================] - 182s 580ms/step - loss: 0.4358 - sparse_categorical_accuracy: 0.8476 - val_loss: 1.0470 - val_sparse_categorical_accuracy: 0.6813\n",
      "157/157 - 5s - loss: 1.0696 - sparse_categorical_accuracy: 0.6786 - 5s/epoch - 32ms/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "[1.0696295499801636, 0.678600013256073]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#编译网络模型\n",
    "model.compile(optimizer='adam',loss=tf.keras.losses.SparseCategoricalCrossentropy(),metrics=['sparse_categorical_accuracy'])\n",
    "#训练网络模型\n",
    "history = model.fit(x_train, y_train, batch_size=128, epochs=10, validation_split=0.2)\n",
    "#评估网络模型\n",
    "model.evaluate(x_test,y_test,batch_size=64,verbose=2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "07939745",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x216 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#读取history的history属性\n",
    "loss=history.history['loss']\t\t\t\t\t#训练集损失函数值\n",
    "#训练集准确率\n",
    "acc=history.history['sparse_categorical_accuracy'] \n",
    "val_loss=history.history['val_loss']\t\t\t#验证集损失函数值\n",
    "#验证集准确率\n",
    "val_acc=history.history['val_sparse_categorical_accuracy']\n",
    "#创建画布并设置画布的大小\n",
    "plt.figure(figsize=(10,3))\n",
    "#在子图1中绘制损失函数值的折线图\n",
    "plt.subplot(121)\n",
    "plt.plot(loss,color='b',label='train')\n",
    "plt.plot(val_loss,color='r',label='validate')\n",
    "plt.ylabel('loss')\n",
    "plt.legend()\n",
    "#在子图2中绘制准确率的折线图\n",
    "plt.subplot(122)\n",
    "plt.plot(acc,color='b',label='train')\n",
    "plt.plot(val_acc,color='r',label='validate')\n",
    "plt.ylabel('Accuracy')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "47f539d1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 10 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "for i in range(10):\n",
    "\tn=np.random.randint(1,10000)\t\t\t\t#生成随机整数n\n",
    "\tplt.subplot(2,5,i+1) \t\t\t\t\t\t#创建子图\n",
    "\tplt.axis(\"off\")\t\t\t\t\t\t\t\t#设置不显示坐标轴\n",
    "\tplt.rcParams['font.sans-serif']=['SimHei']\n",
    "\tplt.imshow(x_test[n],cmap='gray')\t\t\t#绘制图像\n",
    "\tdemo=tf.reshape(x_test[n],(1,32,32,3))\n",
    "\ty_pred=np.argmax(model.predict(demo))\t#应用网络模型\n",
    "\ttitle=\"标签值：\"+str((y_test.numpy())[n,0])+\"\\n预测值：\"+str(y_pred)\n",
    "\tplt.title(title) \t\t\t\t\t\t\t#设置子图标题\n",
    "plt.show()\t\t\t\t\t\t\t\t\t\t#显示图形"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "0521febc-8a6d-4c21-b3a4-f93a2489d452",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c5f80941-6200-4041-8ba7-a4e487efb1df",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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